itkGaussianDensityFunction.h

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/*=========================================================================

  Program:   Insight Segmentation & Registration Toolkit
  Module:    $RCSfile: itkGaussianDensityFunction.h,v $
  Language:  C++
  Date:      $Date: 2005/07/26 15:54:55 $
  Version:   $Revision: 1.15 $

  Copyright (c) Insight Software Consortium. All rights reserved.
  See ITKCopyright.txt or http://www.itk.org/HTML/Copyright.htm for details.

     This software is distributed WITHOUT ANY WARRANTY; without even 
     the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR 
     PURPOSE.  See the above copyright notices for more information.

=========================================================================*/
#ifndef __itkGaussianDensityFunction_h
#define __itkGaussianDensityFunction_h

#include "itkArray.h"
#include "itkVariableSizeMatrix.h"
#include "vnl/algo/vnl_matrix_inverse.h"
#include "vnl/algo/vnl_determinant.h"
#include "vnl/vnl_math.h"

#include "itkMatrix.h"
#include "itkDensityFunction.h"

namespace itk{ 
namespace Statistics{

template< class TMeasurementVector >
class ITK_EXPORT GaussianDensityFunction :
    public DensityFunction< TMeasurementVector >
{
public:
  typedef GaussianDensityFunction Self;
  typedef DensityFunction< TMeasurementVector > Superclass ;
  typedef SmartPointer<Self> Pointer;
  typedef SmartPointer<const Self> ConstPointer;

  itkTypeMacro(GaussianDensityFunction, DensityFunction);
  itkNewMacro(Self);
  
  typedef TMeasurementVector MeasurementVectorType ;

  typedef typename Superclass::MeasurementVectorSizeType MeasurementVectorSizeType;
  
  typedef Array< double >                               MeanType;
  
  typedef VariableSizeMatrix< double >                  CovarianceType;

  void SetMean( const MeanType * mean )
  {
  if( this->GetMeasurementVectorSize() )
    {
    MeasurementVectorTraits::Assert(mean, this->GetMeasurementVectorSize(),
      "GaussianDensityFunction::SetMean Size of measurement vectors in the sample must the same as the size of the mean." );
    }
  else
    {
    this->SetMeasurementVectorSize( mean->Size() );
    }

  if ( m_Mean != mean) 
    {
    m_Mean = mean ;
    this->Modified() ;
    }
  }
  
  const MeanType * GetMean() const
  { return m_Mean ; }

  void SetCovariance(const CovarianceType* cov); 
  
  const CovarianceType* GetCovariance() const ;

  double Evaluate(const MeasurementVectorType &measurement) const ;
  
protected:
  GaussianDensityFunction(void) ;
  virtual ~GaussianDensityFunction(void) {}
  void PrintSelf(std::ostream& os, Indent indent) const;

private:
  const MeanType        * m_Mean;           // mean
  const CovarianceType  * m_Covariance;     // covariance matrix

  // inverse covariance matrix which is automatically calculated 
  // when covariace matirx is set.  This speed up the GetProbability()
  CovarianceType  m_InverseCovariance; 

  // pre_factor which is automatically calculated 
  // when covariace matirx is set.  This speeds up the GetProbability()  
  double m_PreFactor;

  bool m_IsCovarianceZero ;
};

} // end of namespace Statistics
} // end namespace itk

#ifndef ITK_MANUAL_INSTANTIATION
#include "itkGaussianDensityFunction.txx"
#endif

#endif

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